Coreference resolution aims at resolving repeated references to an object in a document
and forms a core component of natural language processing (NLP) research. When used as …

Interpreting anaphoric references is a fundamental aspect of our language competence that
has long attracted the attention of computational linguists. The appearance of ever-larger …

Semantic processing is a fundamental research domain in computational linguistics. In the
era of powerful pre-trained language models and large language models, the advancement …

Teaching computers to solve language problems is one of the major challengesof natural
language processing. There is a large amount of interesting researchdevoted to this field …

Sentence compression holds promise for many applications ranging from summarization to
subtitle generation. Our work views sentence compression as an optimization problem and …

Centering theory is the best-known framework for theorizing about local coherence and
salience; however, its claims are articulated in terms of notions which are only partially …

Many requirements documents are written in natural language (NL). However, with the
flexibility of NL comes the risk of introducing unwanted ambiguities in the requirements and …

In this paper we propose a competition learning approach to coreference resolution.
Traditionally, supervised machine learning approaches adopt the singlecandidate model …

Three experiments examined the hypothesis that it preferentially refers to the most salient
entity in a discourse, whereas that preferentially refers to a conceptual composite. In …

Sentence compression holds promise for many applications ranging from summarization to
subtitle generation. The task is typically performed on isolated sentences without taking the …